DEMO QUESTIONS

Q1: What is the significance of using local ONNX models for embedding within the database?

A: Support for legacy SQL*Plus clients

B: Improved accuracy compared to external models

C: Reduced embedding dimensions for faster processing

D: Enhanced security because data remains within the database

Correct Answer: D

Q2: You want to quickly retrieve the top-10 matches for a query vector from a dataset of billions of vectors, prioritizing speed over exact accuracy. What is the best approach?

A: Exact similarity search using flat search

B: Approximate similarity search with a low target accuracy setting

C: Relational filtering combined with an exact search

D: Exact similarity search with a high target accuracy setting

Correct Answer: B

Q3: Which statement best describes the core functionality and benefit of Retrieval Augmented Generation (RAG) in Oracle Database 23ai?

A: It empowers LLMs to interact with private enterprise data stored within the database, leading to more context-aware and precise responses to user queries

B: It primarily aims to optimize the performance and efficiency of LLMs by using advanced data retrieval techniques, thus minimizing response times and reducing computational overhead

C: It allows users to train their own specialized LLMs directly within the Oracle Database environment using their internal data, thereby reducing reliance on external AI providers

D: It enables Large Language Models (LLMs) to access and process real-time data streams from diverse sources to generate the most up-to-date insights

Correct Answer: A

Q4: You are working with vector search in Oracle Database 23ai and need to ensure the integrity of your vector data during storage and retrieval. Which factor is crucial for maintaining the accuracy and reliability of your vector search results?

A: Using the same embedding model for both vector creation and similarity search

B: Regularly updating vector embeddings to reflect changes in the source data

C: The specific distance algorithm employed for vector comparisons

D: The physical storage location of the vector data

Correct Answer: A

Q5: Which operation is NOT permitted on tables containing VECTOR columns?

A: SELECT

B: UPDATE

C: DELETE

D: JOIN ON VECTOR columns

Correct Answer: D
[acf_quiz]

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